DESCRIPTION

Package: targets.tutorial
Title: Targets Tutorial
Description: Data science can be slow.
  A single round of statistical computation can take several minutes,
  hours, or even days to complete. The 'targets'
  R package keeps results up to date and reproducible
  while minimizing the number of expensive tasks that actually run.
  'targets' learns how your pipeline fits together, skips costly
  runtime for steps that are already up to date, runs the rest
  with optional implicit parallel computing, abstracts files as
  R objects, and shows tangible evidence that the output matches
  the underlying code and data. In other words, the package saves
  time while increasing our ability to trust the conclusions of
  the research. This hands-on workshop teaches 'targets'
  using a realistic machine learning case study.
  Participants begin with the R implementation of a machine
  learning project, convert the workflow into a 'targets'-powered pipeline,
  and efficiently maintain the output as the code and data change.
  The case study comes from an 2018 RStudio AI Blog post by Matt Dancho:
  <https://blogs.rstudio.com/ai/posts/2018-01-11-keras-customer-churn>.
Version: 0.0.1
License: MIT + file LICENSE
URL: https://wlandau.github.io/targets-tutorial,
  https://github.com/wlandau/targets-tutorial,
  https://rstudio.cloud/project/1699460
BugReports: https://github.com/wlandau/targets-tutorial/issues
Authors@R: c(
  person(
    given = c("William", "Michael"),
    family = "Landau",
    role = c("aut", "cre"),
    email = "will.landau@gmail.com",
    comment = c(ORCID = "0000-0003-1878-3253")
  ),
  person(
    family = "Eli Lilly and Company",
    role = "cph"
  ))
Depends:
  R (>= 3.5.0)
Imports:
  cli (>= 2.2.0),
  corrr (>= 0.4.3),
  fst (>= 0.9.4),
  keras (>= 2.3.0.0),
  lobstr (>= 1.1.1),
  pryr (>= 0.1.4),
  qs (>= 0.23.4),
  recipes (>= 0.1.15),
  rmarkdown (>= 2.6),
  rprojroot (>= 2.0.2),
  rsample (>= 0.0.8),
  tarchetypes (>= 0.0.1),
  targets (>= 0.0.1),
  tidyverse (>= 1.3.0),
  usethis (>= 2.0.0),
  visNetwork (>= 2.0.9),
  withr (>= 2.3.0)
Suggests:
  bs4Dash (>= 0.5.0),
  knitr (>= 1.30),
  pingr (>= 2.0.1),
  shiny (>= 1.5.0),
  shinycssloaders (>= 1.0.0),
  testthat (>= 3.0.0)
Remotes:
  ropensci/tarchetypes,
  ropensci/targets
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Config/testthat/edition: 3